Current Approaches to Forecasting Social and Economic Development in Regions: Analysis and Classification
https://doi.org/10.21686/2413-2829-2026-4-130-135
Abstract
Forecasting is a key form of regional policy. The article analyzes different methods of forecasting social and economic development in region, traditional and innovation ones included. Principle approaches are classified in several categories of forecasting, including economic and mathematic models and AI use in analyzing bid data. It was pointed out that use of AI and algorithms of machine learning gives an opportunity to raise accuracy and effectiveness of forecasting social and economic development in regions. In particular, the authors underlined the importance of big data by using neuron nets to analyze complicated interrelations, which can open new horizons in forecasting methods.
About the Authors
O. I. Esina
Plekhanov Russian University of Economics
Russian Federation
Russian Federation
Olga I. Esina, PhD, Associate Professor of the Department for National and Regional Economics
of the PRUE
36 Stremyanny Lane, Moscow, 109992
L. S. Marien
Plekhanov Russian University of Economics
Russian Federation
Russian Federation
Lyudmila S. Marien, PhD, Associate Professor of the Department for National and Regional Economics
of the PRUE
36 Stremyanny Lane, Moscow, 109992
References
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Review
For citations:
Esina O.I., Marien L.S. Current Approaches to Forecasting Social and Economic Development in Regions: Analysis and Classification. Vestnik of the Plekhanov Russian University of Economics. 2026;23(4):130-135. (In Russ.) https://doi.org/10.21686/2413-2829-2026-4-130-135
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